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Hourly water-carbon interactions modulate decadal water-use efficiency trends inferred from ecosystem-scale measurements.

Authors :
Chang, Kuang-Yu
Riley, William J.
Keenan, Trevor F.
Source :
Agricultural & Forest Meteorology. Nov2022, Vol. 326, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

• Water-use efficiency (WUE) inferred from 40 eddy covariance sites was analyzed. • No single ecophysiological factor individually explains the emergent WUE trends. • Higher WUE covering less than 22% of the observational period control WUE trends. • CMIP6 models do not capture factors contributing to the observed WUE trends. Plant stomatal conductance regulates photosynthesis and transpiration. This physiological link affects ecosystem responses to microclimate and harmonizes carbon, energy, and water exchanges between the biosphere and atmosphere. The relationship between water losses via transpiration and carbon gains via photosynthesis can be quantified by plant water-use efficiency (WUE). While leaf- and ecosystem-scale observations both suggest rising WUE in recent decades, WUE trends inferred from the ecosystem scale are much larger than those inferred from the leaf scale or implied by theory. The unexpectedly large ecosystem-scale WUE trends complicate interpretation of ecophysiological responses to changing environmental conditions. Here, we analyze ecosystem-scale WUE inferred from 40 FLUXNET sites, each with at least 10 years of measurements. Our results demonstrate that observed ecosystem-scale WUE trends are more sensitive to hourly weather conditions than longer-term changes in atmospheric carbon dioxide or vapor pressure deficit. Our analysis shows that Earth System Models participating in CMIP6 did not capture the observed WUE sensitivity to inter-site variability and microclimatic conditions. Collectively, our findings suggest that ecosystem-scale WUE trends reflect water-carbon interactions across multiple temporal scales, and disentangling factors contributing to emergent ecosystem responses is needed to infer ecophysiological relationships and model structures from observations. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01681923
Volume :
326
Database :
Academic Search Index
Journal :
Agricultural & Forest Meteorology
Publication Type :
Academic Journal
Accession number :
159599634
Full Text :
https://doi.org/10.1016/j.agrformet.2022.109158